The present apparatus and method relate to video technology, and more particularly to video measurement.
With the proliferation of video formats and devices, changes in image size, registration and cropping occur more frequently. Video reformatting for repurposing is becoming more common. For example, sending 720 sample per line 601 SD video signal as a 704 ATSC digital broadcast signal would require reformatting. Similarly, conversion of a 720 SD video signal similar to that shown in FIG. 1 (Prior Art) to a 1920 HD video signal similar to that shown in FIG. 2 (Prior Art), which result from simulcast SD and HD, also require reformatting. In addition to reformatting due to changing broadcast options, conversion of video for use on mobile phones or PDAs, such as conversion of HD video to QCIF for mobile phones, or PDA video, also require reformatting. This reformatting may require a change in image size, or a spatial shift referred to as registration, or a loss of image near the image borders, also referred to as cropping. Such reformatting can require that images are fit into a new aspect ratio, for example 16:9 versus 4:3. Reformatting can also require truncation, or cropping, on the sides of images, or adding blank border segments on the sides, or above or below the image, for example in the case of letterboxed images. This reformatting presents problems for equipment manufactures, broadcasters, editors, and other video professionals and service providers. Processing equipment may be set in incorrect modes, malfunction, or standards may vary, for example as in the 720 to 704 pixel example provided above.
A measurement instrument capable of executing a method of measuring spatial distortion, scale, offset or shift, and cropping of video output would be useful. In addition, picture quality measurements will also benefit from spatial alignment between a test and reference sequence pair for full reference measurements.
In the past, this has been achieved, at least in part, using a proprietary stripe placed over the original video image. This is intrusive and requires that test and reference video sequences both have the stripe, which requires that the stripe be added prior to video compression or other processing required for transmission, or storage. This has been a limitation of automated picture quality measurement applications, because in some applications it is not practical or desirable to add the stripe once the need for making a measurement arises.
An automated method of measuring spatial distortion for automated video measurement (VM) applications such as consumer electronics video output verification would be useful. A method for automated spatial alignment for use in connection with automatic picture quality (PQ) measurements would also be useful. It would be useful if the method were robust in the presence of digital compression artifacts, random noise, quantization error, nonlinear distortion, linear distortion, and interference. It would also be useful for this method to be able to operate without prior knowledge of the video content, including any stripe added to the video signal, aspect ratio, DUT pixel clock, or other indications of the likely horizontal or vertical scaling, offset or cropping. The practical utility of the method would improve if the method provided both accuracy and computational efficiency. Computational efficiency refers to the amount of processing required to achieve a given accuracy. The less processing required to achieve a desired level of accuracy the better the computational efficiency.
What is needed is an accurate and computationally efficient method of spatial distortion measurement that is robust over a wide range of scale ratios from less than 0.1 to greater than 10.0, significant cropping from less than 0.65 to greater than 1.35 as well as addressing other impairments of the prior art. The spatial distortion measurements that could be made might include spatial scale, shift, as well as cropping in both the horizontal and the vertical dimensions. It would also be useful, if this method could be at least partially, if not entirely, automated.